Telegram RegisterThe public register of Telegram

Channel

Этихлид

@etechlead

On this record: Growth · Engagement · Reactions · Stars · Posts · Citations · Cite this entry

6,699subscribers

+35 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1002028598037
TypeChannel
Username@etechlead
CreatedBetween 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded6 August 2026
Last confirmed live12 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 12 August 2026
On Telegramt.me/etechlead

Growth

6,6646,6996,681.56 August 2026 — 6,664 subscribers7 August 2026 — 6,666 subscribers9 August 2026 — 6,676 subscribers12 August 2026 — 6,699 subscribers6 August 202612 August 2026
4 measurements spanning 7 days, net +35. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 6,659–6,704 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
12 Aug 2026, 21:186,699+23
9 Aug 2026, 23:316,676+10
7 Aug 2026, 02:276,666+2
6 Aug 2026, 04:326,664first reading

Engagement

15 posts held, back to 5 June 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 9 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
50.5%
avg views ÷ 6,699 subscribers
Avg views / post
3,390
2 posts measured
Reaction rate
2.79%
reactions ÷ views · ER floor
Posts in window
2
of 15 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views— note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.

What these figures were computed from
WindowRolling 30 days · latest post in window 8 August 2026
Posts held15 (5 June 20268 August 2026)
Views total6,770
Reactions total189
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken12 Aug 2026, 02:54 UTC

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

Reaction mix

863 reactions across 15 posts, in 14 distinct kinds. The most used accounts for 35.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
🔥31035.9%
👍23927.7%
18721.7%
😁313.59%
👏273.13%
💯202.32%
🎉192.20%
❤‍🔥171.97%
60.695%
👌20.232%
🫡20.232%
🕊10.116%
😢10.116%
🤩10.116%

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 15 of the 15 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 863reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 5 June 2026 to 8 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Telegram Stars

Stars received
15
across the posts below
Posts paid on
3
of 15 we hold a reading for · 20%
Most on one post
7
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @etechlead. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.

Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.

This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.

Counted over the 15 most recent posts we hold for this entry, published 5 June 2026 to 8 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.

Recent posts

8 Aug 2026, 19:39 UTC≈2,600 views85 reactionsread 12 August 2026

The Jeff Dean Facts Из Google после 27 лет работы ушёл Джефф Дин - вместе с несколькими коллегами идёт строить Discovery Loop - стартап про ускорение научных исследований с помощью ИИ. Для меня Джефф - это инженер-легенда и один из тех редких профи, на которых всегда хотелось быть похожим. И не из-за должностей и регалий, а потому, что за ним стоят такие проекты, как Google Search, MapReduce, Bigtable, Protocol Bu

🔥41😁25👍9❤‍🔥8🫡2

17 Jul 2026, 12:08 UTC≈4,170 views104 reactionsread 12 August 2026

Последний программист Года полтора назад, в одном из постов, я объявлял в розыск рассказ про деда-программиста, который назло всесильному ИИ продолжал писать код руками. Докладываю: рассказ найден, называется "Последний программист", автор - Герберт В. Франке. Публиковался в Компьютерре в 2001м. А до этого ещё и в "Наука и жизнь" в 1990м (ссылки ведут именно на эту версию). А написан он вообще в 1981м! Так вот, и

59🔥28👍14👏2🤩1

12 Jul 2026, 13:29 UTC≈4,190 views48 reactionsread 12 August 2026

AMA команды Codex после релиза GPT-5.6 Команда Codex провела AMA на Reddit после релиза GPT-5.6 и нового приложения ChatGPT+Codex, которое теперь будет универсальной рабочей средой - и для кодинга, и для других рабочих задач, с браузером, внешними коннекторами и субагентами. Вот самые интересные, на мой взгляд, ответы команды с моими комментами: ⚪️ Как выбирать модели GPT-5.6 ● Sol - основная модель ● Terra - быст

20🔥14👍10👏3🎉1

30 Jun 2026, 10:43 UTC≈5,010 views84 reactions7 Starsread 12 August 2026
Photo

Перевёл документ от Google, который описывает текущую ситуацию по переходу от "бессистемных промптов к агентной инженерии": ➡️ Новый SDLC с вайб-кодингом Это первый, самый общий и концептуальный, из пяти whitepaper'ов бесплатного курса 5-Day AI Agents: Intensive Vibe Coding Course от Google и Kaggle. Бонусом там ещё и глоссарий терминов/переводов получился. Это база В нём качественно суммируется то, что разработк

👍42🔥2713❤‍🔥1🕊1

27 Jun 2026, 15:35 UTC≈3,370 views70 reactionsread 12 August 2026

Вопросы "в глубину" к стартовым задачкам (2/2) Прокся для доступа к нейронкам (типа OpenRouter) ⭐️⭐️⭐️ Хорошая задача, и опять же почти целиком инженерная. Сам я тут обходился готовым, так что вдвойне было бы интересно послушать тех, кто полез делать своё - что именно не закрыл OpenRouter/LiteLLM. ● как справлялись с зоопарком вендорских API? ● что делали, когда вендор отвечает 429? ● по какому признаку роутили ме

👍35🔥199💯4👏3

27 Jun 2026, 15:35 UTC≈2,350 views48 reactionsread 12 August 2026

Вопросы "в глубину" к стартовым задачкам (1/2) На самом деле, если вы занимались вышеперечисленными задачами, вы знаете, что они практически все с подвохами :) И это делает их хорошими для того, чтобы копать вглубь на, к примеру, собеседовании на AI-assisted SWE. Опишу, что же ценного может быть в каждой из них в формате вопросов для беседы с потенциальным кандидатом. Ключевое для меня, пожалуй, в том, чтобы задач

👍18🔥159🎉3👏3

20 Jun 2026, 19:40 UTC≈3,700 views40 reactionsread 12 August 2026

Posted without readable text

💯16🔥10👍7😁6😢1

20 Jun 2026, 19:40 UTC≈3,190 views28 reactionsread 12 August 2026

В программировании всегда были такие задачи, за которые часто брались новички. Некоторые из них оказывались крайне ценными для становления специалиста, а где-то это был весёлый бег по граблям и изобретение велосипедов. Для вайбкодинга тоже накопилось некоторое количество подобных мемных задач, мимо которых сложно пройти. Давайте попробуем собрать статистику. P.S. Ну и напишите, может есть ещё что-то такое, что дол

👍1364🔥3👌2

17 Jun 2026, 17:45 UTC≈4,360 views83 reactions6 Starsread 12 August 2026

AI-вангование, итоги 8 месяцев назад довелось мне поучаствовать в круглом столе на FrontEnd Conf 2025, где мы обсуждали тему внедрения AI в SDLC. А недавно Глеб сообщил о том, что записи наконец выложили в открытый доступ, так что теперь есть чем поделиться :) Пересказывать видео не буду, советую всё-таки посмотреть - дискуссия во многом всё ещё актуальная: Круглый стол про AI в SDLC Лучше сделаю вот что. Готовя

🔥3822👍15👏6🎉2

15 Jun 2026, 10:32 UTC≈3,710 views59 reactionsread 12 August 2026
Photo

AgenticOps, часть №4 - агенты и сценарии Тут расскажу про основных агентов, которые пользуются платформой - у них разные роли и доступные сценарии. Роль агента приходит как внешний по отношению к CLI параметр (через конфиг или переменную окружения) и, по сути, ограничивает список доступных агенту команд в определённом контексте. Т.е. агент ещё на этапе discovery видит только те команды, которые ему можно вызывать,

🔥29👍18❤‍🔥7🎉32

11 Jun 2026, 18:49 UTC≈4,180 views37 reactionsread 12 August 2026
Photo

Сработаемся? Навеяно обсуждением бенчмарков на недавнем стриме и тестированием Fable. Смотрите, какая штука: кажется, фронтирные модели уже пересекли планку "достаточно" для "средних" задач во многих проектах по разработке. А раз модели выдают решения, разницы между которыми по качеству не видно, то выбор перестаёт быть вопросом оценки модели в абстрактных попугаях. Вместо этого на первый план выходит характерист

🔥17👍106👏3❤‍🔥1

9 Jun 2026, 14:09 UTC≈3,580 views49 reactionsread 12 August 2026
Photo

AgenticOps, часть №3 - платформа Общие принципы ● агенты общаются с платформой через CLI + SKILL.md ● CLI-команды - плоские и максимально простые ● топология ресурсов приложения инкапсулирована в платформе ● даём агенту высокоуровневые инструменты, но стараемся избегать дырявых абстракций ● у агента могут быть как платформенные тулы, так и специфичные для его локального контекста ● почти всё типизировано, компилируе

🔥2714👍4🎉3👏1

Showing the 12 most recent of 15 posts we hold for @etechlead. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.

Citation-graph rank

Citation-graph rank — 38,300 of 1,160,990entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Republishes

Channels on the register whose posts this channel has forwarded.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 16 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.

A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 12 August 2026 — this entry's latest reading, not the date you are reading this.

“Этихлид” (@etechlead), 6,699 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/etechlead.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.